Robust efficient method of moments estimation

This paper focuses on the robust Efficient Method of Moments (EMM) estimation of a general parametric stationary process and proposes a broad framework for constructing robust EMM statistics in this context.. We characterize the local robustness properties of EMM estimators for time series by computing the corresponding influence functions and propose two versions of a robust EMM (REMM) estimator with bounded influence function. We then show by Monte Carlo simulation that our REMM estimators are very successful in controlling for the asymptotic bias under model misspecification while maintaining a high efficiency under the ideal structural model.